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Data Science Blog > R > Financial Metrics Dashboard for U.S. Companies

Financial Metrics Dashboard for U.S. Companies

hderouen1
Posted on Apr 4, 2025

Introduction

In today’s data-driven finance world, investors and analysts are overwhelmed with information. It can be difficult to find meaningful trends or compare company performance effectively. This interactive R Shiny app was designed to solve that problem.

The application allows users to explore financial metrics for major U.S. companies from 2009 to 2023. It supports deep analysis, fast comparisons, and clear visual insights.


Data Overview

This project uses financial data from 2009 to 2023. The dataset includes well-known, publicly traded companies. It tracks a wide variety of metrics:

  • Revenue
  • Net Income
  • Earnings Per Share (EPS)
  • Return on Equity (ROE)
  • Return on Assets (ROA)
  • EBITDA
  • Debt-to-Equity Ratio
  • Operating Cash Flow
  • Market Capitalization

These variables help users explore trends, assess performance, and uncover operational strengths or weaknesses.

 


Project Goals

This app makes financial performance analysis more accessible. Users can:

  • Analyze how metrics change over time
  • Compare multiple companies easily
  • Identify patterns in growth and profitability
  • Investigate the relationships between key financial ratios

 


Key Questions the App Answers

  • Which companies have grown consistently over time?
  • How have metrics like ROE or Net Income evolved?
  • What impact did economic cycles have on performance?
  • Are there correlations between profitability and efficiency?

These questions guide users toward useful, data-backed conclusions.


App Features and Interface

Filtering and Customization

Users can filter by company, financial metric, and year range. This allows for highly specific analysis and customized exploration.

Rolling Averages for Trend Clarity

The app applies rolling averages to smooth out data fluctuations. As a result, long-term patterns become easier to spot.

 

Comparative Bar Charts

Bar charts show relative performance between companies. For example, users can compare total Net Income across three firms.

 

Summary Tables with Conditional Formatting

Tables display key statistics like mean, max, min, and growth rate. Color formatting highlights positive and negative trends:

  • Green indicates positive growth
  • Red indicates negative growth

 

Scatterplots and Heatmaps

Scatterplots let users explore relationships like ROE versus ROA.

Heatmaps help visualize how a selected metric varies across companies and years.

 

Boxplots for Metric Distribution

Boxplots display the distribution and variation in financial performance. This helps identify outliers and high-performing companies.


Technologies Used

  • R
  • shiny (for interactivity)
  • ggplot2 and plotly (for visualizations)
  • dplyr and zoo (for data wrangling and time series smoothing)
  • DT (for interactive tables)

Example Use Case

Let’s say a user wants to compare the ROE and Net Income of three companies between 2010 and 2020. The app lets them:

  1. Choose the companies
  2. Set the year range
  3. Select metrics like ROE and Net Income
  4. View summary tables, charts, and trends

 


Insights and Takeaways

Using the app, users can:

  • Spot trends in financial growth
  • Identify companies with stable or fluctuating performance
  • Compare efficiency across companies using ratios
  • Discover patterns that inform investment decisions

The visual nature of the app makes it easier to interpret complex data.


Future Enhancements

To improve the experience further, the following features may be added:

  • Filters by industry or sector
  • Additional metrics like P/E Ratio or Current Ratio
  • Forecasting tools for predictive insights
  • User-uploaded datasets for custom analysis

Conclusion

This dashboard makes financial analysis easier, more visual, and more interactive. Whether you are an investor, student, or analyst, this app helps turn raw data into valuable insights.

By combining clean design with analytical power, it transforms spreadsheets into stories.


Access the App

Ready to try it? Visit the live app here:

[shinyapp_link]

 

[Github Link]

About Author

hderouen1

View all posts by hderouen1 >

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